AI Agents Deep Dive
Understanding AI agents from fundamentals to multi-agent systems and building your own in TypeScript.
11 articles101 min total read time
11 of 11 posts published
01
AI Agents Explained: A TypeScript Developer's Guide
AI agents use LLMs to complete multi-step tasks autonomously. Here is how they work and how to build them in TypeScript.
6 min read|Read →
02
How to Build AI Agents in TypeScript
A practical guide to building AI agents with TypeScript using the Vercel AI SDK. Tool use, multi-step reasoning, and real patterns you can ship today.
10 min read|Read →
03
Multi-Agent Systems: How to Orchestrate Multiple AI Agents in TypeScript
From swarms to pipelines - here are the patterns for coordinating multiple AI agents in TypeScript applications.
6 min read|Read →
04
The Agentic Development Tech Stack for 2026
Coding changed more in the past two years than in the previous decade. We moved from manual typing to autocomplete, then to multi-file edits.
12 min read|Read →
05
AI Agent Frameworks Compared: LangGraph vs CrewAI vs AutoGen vs Claude Agent SDK vs Vercel AI SDK
A practical comparison of the five major AI agent frameworks in 2026 - architecture, code examples, and a decision matrix to help you pick the right one.
14 min read|Read →
06
How to Debug AI Agent Workflows
AI agents fail in ways traditional debugging cannot catch. Here are the tools and patterns for finding and fixing broken agent loops, tool failures, and context issues.
9 min read|Read →
07
AI Agent Memory Patterns
Agents forget everything between sessions. Here are the patterns that fix that: CLAUDE.md persistence, RAG retrieval, context compression, and conversation summarization.
9 min read|Read →
08
Over-Editing: Why Your AI Coding Agent Rewrites What Isn't Broken
A new study from nrehiew quantifies a problem every Claude Code, Cursor, and Codex user has felt: models making huge diffs for tiny fixes. Here is why it happens, why tests do not catch it, and what to do about it.
8 min read|Read →
09
Intent Debt: The AI-Era Debt Nobody Is Tracking
Martin Fowler reframes AI-era debt into three layers - technical, cognitive, and intent. The third one is the one most teams are silently accumulating. Here is what it is and how to diagnose it.
8 min read|Read →
10
7 AI Agent Orchestration Patterns Every Developer Should Know
From single-agent baselines to multi-level hierarchies, these are the seven patterns for wiring AI agents together in production. Each with a decision rule, an implementation sketch, and the tradeoffs that actually matter.
10 min read|Read →
11
The Agent Reliability Cliff: Why Your 10-Step Chain Only Succeeds 20% of the Time
The math of agent pipelines is brutal. 85% reliability per step compounds to about 20% at 10 steps. Here is why long chains collapse in production, and the six patterns the field has converged on to fight the decay.
9 min read|Read →
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